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Complexity theory has been used in the fields of strategic management and organizational studies. Application areas include understanding how organizations or firms adapt to their environments and how they cope with conditions of uncertainty. The theory treats organizations and firms as collections of strategies and structures. The structure is complex; in that they are dynamic networks of interactions, and their relationships are not aggregations of the individual static entities. They are adaptive; in that the individual and collective behavior mutate and self-organize corresponding to a change-initiating micro-event or collection of events.[1][2]

CAS are contrasted with ordered and chaotic systems by the relationship that exists between the system and the agents which act within it. In an ordered system the level of constraint means that all agent behaviour is limited to the rules of the system. In a chaotic system the agents are unconstrained and susceptible to statistical and other analysis. In a CAS, the system and the agents co-evolve; the system lightly constrains agent behaviour, but the agents modify the system by their interaction with it. This self-organizing nature is an important characteristic of CAS; and its ability to learn to adapt, differentiate it from other self organizing systems.[1]

CAS approaches to strategy seek to understand the nature of system constraints and agent interaction and generally takes an evolutionary or naturalistic approach to strategy. More recently work by organizational scholars and their colleagues have added greatly to our understanding of how concepts from the complexity sciences can be used to understand strategy and organizations. Much of this later research integrates computer simulation and organizational studies.